In the present work, the WorldView-2 (WV2) capability for retrieving Case 2 water components is analyzed.
The WV2 sensor characteristics, such as a 11-bit quantization, 8 bands in the VNIR (visible and near infrared)
region and high Signal-to-Noise Ratios (SNR) make WV2 potentially suitable for a retrieval process. In the
Case 2 water problem, the sensor-reaching signal due to water is very small when compared to the signal due
to the atmospheric eects. Therefore, adequate atmospheric compensation becomes an important rst step to
accurately retrieve water parameters. The problem becomes more dicult when using multispectral imagery as
there are typically only a handful of bands suitable for performing atmospheric compensation. In this work, we
test atmospheric compensation techniques for the WV2 satellite, enabling it to be used for water constituent
retrieval in both deep and shallow water. A look-up-table (LUT) methodology is implemented to retrieve the
water parameters chlorophyll, suspended materials, colored dissolved organic matter, bathymetry, bottom type
and water clarity for a simulated case study. The in-water radiative transfer code HydroLight is used to simulate
ectance data in this study while the MODTRAN code is used to simulate atmospheric eects. The resulting
modeled sensor-reaching radiance data can be sampled to a WV2 sensor model to simulate WV2 image data.
This data is used to test the proposed methodology. Finally, a sensitivity analysis is performed to evaluate how
sensitive the constituent retrieval process is to adequate atmospheric compensation.